Download - Nco Role In Battlefield Management
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Navneet Bhushan
Crafitti Consulting (www.crafitti.com)
CAIR, DRDO, August 10, 2010
A visualization of the network structure of the Internet at the level of “autonomous systems”—local groups
of computers each representing hundreds or thousands of machines. Picture by Hal Burch and Bill Cheswick, courtesy of Lumeta
Corporation. INTERNET
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August 16, 2010 2© Crafitti Consulting Private Ltd.
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August 16, 2010 3© Crafitti Consulting Private Ltd.
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August 16, 2010 4© Crafitti Consulting Private Ltd.
The Singaporean designer Fung Kwok Pan has managed to capture
the flow of water in solid form, and the results are stunning.
http://www.fastcodesign.com/1662020/eye-candy-solid-
vase-is-a-3-d-pic-of-splashing-milk
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August 16, 2010 5© Crafitti Consulting Private Ltd.
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Globe has been Re-engineered!
Flattening World
… And we don’t even realize it …
While the defining measurement of (old world)
was weight – … – the defining measurement of
the globalization system is speed – speed of
commerce, travel, communication and
innovation
Thomas L. Friedman, “The Lexus and Olive Tree”
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Power SystemViolence
Wealth
Knowledge
Knowledge based Violence &
Wealth
Violence & Wealth based
knowledge
Structure of
Future
World
Technological SystemsInformation Technology
Industrial Automation
Genomics
Bio-Technology
Smart Materials
Nanotechnology
Propulsion Technology
Geo Political SystemBipolarity/ Multi-polarity
Multinational Companies
controlling the world
Reducing Value of Nation State
Social SystemRise of the Individual/Ethnic/Religious
groupings
Nuclear/Single parent family system
Rise of dissatisfaction
Economic SystemSmall more Networked
Organizations
Rapid Changes in the way wealth
is generated
Low tariff barriers
Common Currencies and
compatible economic systems
Low entry barriers
Organization FormsHierarchies shifting to
Networked form of
Organization
Hierarchical Networks
Networked Hierarchies
SOURCE: Bhushan N. and Rai K., Strategic Decision Making, Springer Verlag, Jan 2004
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The Globalized World
• Global Real-time Awareness
• Large monolithic structures to small, distributed well-connected organizations –Collabtetion –Collaboration+Competition
• Hierarchies – Hierarchical Networks – Networked Hierarchies – Networks
• Power shifts to Knowledge Based Real-time Actors
• Time, Trade, Space, Geography, Cultural, Language, Social Shackles Demolished
• Survival of the Agile – Decision Making and Action at Electronic Speed
• Everyone has the wherewithal to continuously Re-invent oneself
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August 16, 2010 9© Crafitti Consulting Private Ltd.
As economic fortunes rise, so does nationalism
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August 16, 2010 10© Crafitti Consulting Private Ltd.
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August 16, 2010 11© Crafitti Consulting Private Ltd.
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Complexity in a FlatteningWorld
Number of alternatives
Time pressure
Need for analysis
Information de-coherence
Connections
Networks
Human Processing Limits
(The Magic Number 7 ± 2)
Framing Limits
Confidence
Rapid Explosion
of Complexity
Connections create Value and Dependencies
create complexity
Future is approaching us Faster than History is
leaving us!
Increasing distance between user requirements
of what they really need versus what they want.
With every choice we make today we Kill
many possible futures
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Decision Making in a Flattening World
Number of alternatives
Time pressure
Need for analysis
Information de-coherence
Connections
Networks
Human Processing Limits
(The Magic Number 7 ± 2)
Framing Limits
Confidence
Rapid Explosion
of Complexity
Each Decision (a Choice) affects future
Choices (decisions)
Each Decision is impacted by past Decisions
(Choices) made by someone somewhere
With every choice we make today we Kill
many possible futures
With every choice we make today we Select
only a small subset of possible futures
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The Magical Number Seven, Plus or Minus Two:
Some Limits on our Capacity for Processing Information
George A. Miller (1956)
Harvard University
First published in Psychological Review, 63, 81-97.
[1] This paper was first read as an Invited Address before the Eastern Psychological Association in Philadelphia on April 15, 1955.
The point seems to be that, as we add
more variables to the display, we
increase the total capacity, but we
decrease the accuracy for any
particular variable. In other words,
we can make relatively crude
judgments of several things
simultaneously.
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The first decade of 20th Century…
• In 1890, Average company in US had - FOUR employees (4)
• By 1901, US Steel became world’s first 1 Billion $ company
• Ford Motor Company, founded in 1903, was producing half a million cars a by 1913
August 16, 2010 15© Crafitti Consulting Private Ltd.
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The first decade of 21st Century…
August 16, 2010 16© Crafitti Consulting Private Ltd.
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More is Different – Scale is the New Frontier
August 16, 2010 17© Crafitti Consulting Private Ltd.
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SEI ULS Study – 2006!
August 16, 2010 18© Crafitti Consulting Private Ltd.
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Why we don’t know how to Design ULSS?
August 16, 2010 19© Crafitti Consulting Private Ltd.
System Design - Present ApproachesAll conflicts must be resolved centrally and uniformly
Requirements can be known in advance and change slowly.
Tradeoff decisions will be stable.
Discrete Time System improvements
Effect of a change can be predicted sufficiently well.
Configuration information
Components and users are fairly homogeneous.
People are just users of the system.
Collective behavior of people is not of interest.
Social interactions are not relevant.
Failures will occur infrequently. Defects can be removed.
A prime contractor is responsible for system development,
operation, and evolution.
ULS CharacteristicsDecentralized Control
Inherently conflicting, unknowable,
and diverse requirements
Continuous evolution and
deployment
Heterogeneous, inconsistent, and
changing elements
Erosion of the people/system
boundary
Normal Failures
New paradigms for acquisition and
policy
?
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20© Crafitti Consulting Private Ltd.
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August 16, 2010 21© Crafitti Consulting Private Ltd.
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ULSS Research Areas
August 16, 2010 22© Crafitti Consulting Private Ltd.
ULS Systems
Research Area
Specific Sub-Areas
Human Interaction
• Context-Aware Assistive computing
• Understanding Users and Their Contexts
• Modeling Users and User Communities
• Fostering Non-Competitive Social
Collaboration
• Longevity
Computational
Emergence
• Algorithmic Mechanism Design
• Metaheuristics in Software Engineering
• Digital Evolution
Design
• Design of All Levels
• Design Spaces and Design rules
• Harnessing Economics to Promote Good
Design
• Design Representation and Analysis
• Assimilation
• Determining and Managing
Requirements
Computational
Engineering
• Expressive Representation Languages
• Scaled-Up Specification, Verification, and
Certification
• Computational Engineering for Analysis
and Design
Adaptive
System
Infrastructure
• Decentralized Production Management
• View-Based Evolution
• Evolutionary Configuration and
Deployment
• In Situ Control and Adaptation
Adaptable and
Predictable
System Quality
• Robustness, Adaptation, and Quality
Attributes
• Scale and Composition of Quality
Attributes
• Understanding People-Centric Quality
Attributes
• Enforcing Quality Requirements
• Security, Trust, and Resiliency
• Engineering Management at Ultra-
Large Scales
Policy,
Acquisition,
and
Management
• Policy Definition for ULS Systems
• Fast Acquisition for ULS Systems
• Management of ULS Systems
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Competitive Advantage- Over Ages
Time
Ex
tent of
Connec
tednes
s
How much of
Agricultural land
and Natural
Resources
How much can
be produced
How much and
Quickly can be
Informed
How much
Actionable
Knowledge
How Fast
Innovate
How Fast
Co-Create
In the Connected Age –
Co-Creators will thrive
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c r a f t i n g i n n o v a t i o n t o g e t h e rNature is
Fractal!
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Black Swan – The impact of the highly improbable
• “I cannot accept a pretense of science. I much prefer a sophisticated craft, focused on tricks, to a failed science looking for certainties” Nassim Nicholas Taleb
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© CRAFITTI CONSULTING
A Weakening of Hierarchies
• Information abundance permits INDIVIDUALS to by-pass hierarchies that have – deliberately or inadvertently – controlled or limited information
• Alternative human organization forms – based mainly on the Network have proved more effective and efficient for transacting information than hierarchies.
• In Information intensive enterprises, hierarchical organizations may not be competitive with networks.
IN ATHENA’s CAMP – Preparing for conflict in the Information Age, (Ed)
Arquilla J. and Ronfeldt D, RAND, 1997
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© CRAFI
ONLY Networks
CAN FIGHT Networks
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Combat
Fight/Duel/Conflict/Battle/War/World
War/Armageddon
Modelling
Representing a system and its internal and/or external
dynamics in such a form (may be mathematical) that
information about its behaviour can be extracted or
studied
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Parameters and Processes of Combat
• Two Sides
• Search
• Detection
• Identification
• Acquisition
• Tracking
• Weapon Target Assignment
• Weapon Aiming and Firing
• Attrition
• Command and
Control
• Damage
Assessment
• Strategic and
Tactical
Movement
• Influence of
Technology
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Nature of Combat and Combat Models
Past : Numerical Strength is Combat Power/ Attrition
Based
Modelling: Lanchester Equations Based and Fire Power
Scores in QJMA
Present: Technology Based Platform-Centric Revolution
in Military Affairs
Modelling: Weapon Power Scores in Extended Adaptive
Dynamic Model
Future: Network Centric Warfare
Modelling: Exploring New Models
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Approaches to Combat Modelling
Analytical Methods
• Lanchester Equations
• Adaptive Dynamic
Model
Firepower Scores
• QJMA
• WEI
• Weapon Power Scores
Simulation
• Combat
Simulations
• Wargames
New Approaches
• Cellular Automata
• Petri Nets
• Artificial Life
• Particle Swarm
Optimization
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Rand Report MG 268 (http://www.rand.org)
August 16, 2010 33© Crafitti Consulting Private Ltd.
More than 12000 Sorties flown in mid 1990s to compare JTIDS datalink 16 system with conventional voice only communications
250% IMPROVEMENT
IN Kill Ratio
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August 16, 2010 34© Crafitti Consulting Private Ltd.
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Performance Evaluation of an Air Defence System (Networked) Modelled as a Petri Net (1998)
August 16, 2010 35© Crafitti Consulting Private Ltd.
Delay
Arrival
Penetration
No response
Fighter
SAM
Gun
AD1
AD2
AD3
CAOC
CAOC
ACC
ACC
ACC
CAOC
TL3
TR2
TR1
TL3
BOR DERBOR DERBOR DER
Enemy AircraftAirborne radar
Mobile radar
Radar
Sensor Fusion Post (SFP)
ACC1
ACC2
SFP2
SFP3Central Air Operation
Centre (CAOC)
AIR CONTROL
CENTRE
(ACC)
SAM
OP
Centrel
SHORAD
OPERATION
CENTRE
FIGHTER
SQUADRON
OP CENTRE
SAM
Site
Air Defence
Guns
Fighter
Squadron
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August 16, 2010 36© Crafitti Consulting Private Ltd.
Delay Delay StartStop Arrival
Limit
300 .Arrivals
Arrival
Threats
DetectedUndetected
Back Sensor
Undetected
PenetrationsPenetration
TX1
SFP
TL
Gone1
Gone2CAOC
ACC
NS
Plane
No response
ACCL
TR
ACCRSAM
Gun
Sqdn
SAMOC
Fighter Plane
SAM
Gun
Pres
Sres
Gres
SHORADOC
NG
NP
ACC
TX2
Transition with exponential firing
Transition with determinstic firing
Fig. 3 : TTPN Model of an AD System
Time Transition Petri Net Model of an AD System
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Penetration Probability Vs Arrival Rate
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Application- Simulation of Terrorist Networks and Evaluation of Strategies
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Destabilization Strategies
Each strategy identifies actor criticality in a different way. All strategies rely on data in one or more cells in the meta-matrix. The identified strategies are:
• Highest degree centrality: Isolate one agent from the covert network that has the highest degree centrality [20].
• Highest betweenness centrality: Isolate one agent from the covert network that has the highest betweenness centrality [20].
• Highest cognitive load: Isolate one agent from the covert network that has the highest cognitive load [6], where cognitive load is computed as a linear combination of:
– Number of people person i interacts with / total number of people in the group;
– Number of subtasks person i is assigned to / total number of subtasks;
– Sum of number of people who do the same tasks person i does / (total number of tasks * total number of people);
– Sum of negotiation needs person i needs to do for each task / total possible negotiations, where a negotiation corresponds to the amount of information or resources that an agent needs to complete a subtask that it is assigned to, but doesn't have (and thus has to obtain from another agent by negotiation).
• Highest task accuracy: Isolate the best performing agent in the organization. This corresponds to standard police practice of arresting agents implicated in commission of a terrorist act.
• Amount of unique knowledge: Isolate the agent that has the highest expertise.
© Crafitt
39
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NetWatch: A Multi-Agent Network Model of Covert Network Surveillance and Destabilization
© Crafitt
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• Random case consisted of random removal strategy combined with one of the three wiretapping strategies. The baseline increases with accuracy of network discovery because of the fact that learning more of the network gives the random strategy better access to targets (including these of high importance). In the absence of false positives, the baseline strategies perform better then many complex heuristics.
• Degree Centrality-based removal of agents performs well only with targeted wiretapping. This is because targeted wiretapping allows the Blue Team to completely discover a cell and all of its neighborhood, and thus be very confident in removal of a most central person. However, the network does recover reasonably quickly from the hit, thus decreasing the effectiveness of this strategy.
• Betweenness Centrality-based removal performs well with roving wiretaps - because of the fact that they allow quick location of key gatekeepers in the network.
• Cognitive Load-based removal requires significant knowledge of the network, and thus only performs well under targeted and roving wiretap strategies.
• Quite surprisingly, removal of Well-Performing individuals did not result in significant damage to the terrorist network. Most likely this is caused by the structure of the tasks that the agents perform and equivalence of individuals in equivalent network positions.
• Knowledge-based removal proved to be the most effective strategy of the lot, and the only one to outperform the baseline strategies. The key to knowledge-based removal, though, is that its effectiveness hinges on speed of response more than the accuracy of structural knowledge. The experiments show that the highest efficiency of this strategy is achieved if Red Team experts are found and removed before they transmit much of their knowledge to the rest of the group, thus favoring quick decisive action to lengthy deliberation and heuristic learning that are characteristic of roving wiretaps.
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The Past
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Combat
• Duels
• LOS Fire
• Attrition Based Warfare
• Numerical Strength
Important (the 3:1 Rule)
To make a Brigade of 4000 troops ineffective, one
needs to destroy atleast 33% to 50% of its troops
using a Division of about 12000 troops
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Combat Models: Past
• Coupled Differential Equations
incorporating the rate at which both sides
destroy each other’s numerical strengths
• Quantified Judgement Method of Analysis
based on Empirical Formulae developed
using Historical Combat Data of Past
Wars (T.N. Dupuy)
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The Present
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Influence of Technology on War/Combat
Information Technology
C4ISR IW/EW/SEW
PGMs ILSS
Knowledge Processing
Intelligence Analysis
Tactical and Strategic
Planning
Automated/Rapid Military
Decision Making
Telecom & Networking
Communications
NetWar/CyberWar
Mobile Comm
Lethality
Mass Destruction to
Selective/Precise &
Effective Destruction
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COLLECT &
PROCESS
BATTLEFIELD
INFORMATION WITH
SPEED AND
ACCURACY
CAPABILITY TO
PICK OUT
TARGETS IN A
DYNAMIC BATTLE
SCENARIO
ABILITY TO DESTROY
TARGETS WITH
PRECISION FROM
GREATER RANGES
HEART OF REVOLUTION IN MILITARY AFFAIRS
(RMA)
INTERACTION
ABILITY TO SEE / CHOOSE TARGETS BETTER
INCREASES THE EFFECTIVENESS OF
PRECISION GUIDED MUNITIONS
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The Future
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Network Centric Warfare
Network is the Computer
Fundamental Shift from Platform Centric
warfare to Network Centric Warfare
Characterized by:
Very High Level of Shared Battlespace
Awareness
Shared Knowledge of Commanders Intent
Self-Sync, Speed of Command, and rapid lock-
out
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Network Centric Warfare:
Sources of Increased Combat Power
Shared Battlespace Awareness
Increased Battlespace Awareness
Battlespace Expansion: Employment of
Weapons at Max Range
Increased Survivability
Self-Synchronization of Forces
Reduced Collateral Damage
Virtual Collaboration: Moving Information not
people
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Modelling and Analysis of
Advanced Technologies and
Combat Support Systems in
Combat between RMA Forces
The Present
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Evaluation of Weapon
Power Scores of Army,
Navy and Air Force
Weapons
Combat
Support System
(CSS)
Capability
Assessment
Combat
Outcomes
CSS Weights
based on AHP
Force Multiplier
related to CSSEstimation of
Quantity of
Weapons
Force Strength
Evaluation
Generation of
Combat Scenarios
Adaptive
Dynamic
Model
Estimation of
Model
Parameters
M E T H O D O L O G Y
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Weapon Power Score
Self
Protection
Index
Integration
IndexLethality Operability
Index
On-Board
Weapons
Capability
On- Board Self
Defence
Capability
Night / All
Weather
Capability
Ability to get
connected to
C3I System
Each Node in the Network
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= Operational Lethality Index (OLI) x (1+ Self-Protection Index (SPI)) x
(1 + Operability Index (OI)) x (1 + Integration Index (II))
Weapon Power Score (WPS)
Force Strength (FS)
= Summation of product of WPS and Quantity of weapons in a force
Force Potential (FP)
= Force Strength x (1 + Combat Support System Effectiveness Factor)
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Factors considered for OLI Computations
Weapons Factors
Infantry Small Arms
and Non Mobile
Weapons
Rate of Fire, Range, Accuracy, Reliability,
and Potential Targets per Strike, Dispersion
Factor
Arty Towed/AD Guns All of the above and certain Artillery
related factors
Arty Self-Propelled All of the above and Mobility factors.
Armour, Ships,
Submarines
OLI of on-board Guns and Missiles,
Mobility factor Punishment factor,
Ammunition factor, Amphibious
capability factor etc.,
Attack Helicopter,
AircraftOLI of on-board Guns, Missiles, Ceiling
factor Mobility factor,
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Factors Affecting SPI, OI and II of Army Platforms
Weapon System Factors Affecting
SPI IIOI
Infantry Survivability Night Vision,
Transportability
Communication Links
with Brigade. HQ. and
RPV/UAV
Armor
Built-in-Armor,
Reactive Armor, Top
Attack Protection NBC
Protection, Fire &
Explosion Suppression,
Silhouette, Agility
Night Vision, All
Weather Operations,
fording,
Amphibious
Capability, Air
droppable
Communication Links
with RPV/UAV and other
Armor Vehicles.
Artillery GunsShoot & Scoot
Capability, Stand Off
Range, Armored
Protection
All weather
Operability, NBC
Operability.
Integration with AOP
AD Arty/ SAMShoot & Scoot
Capability, Stand Off
Range
Radar Control, NBC
Environment
Integration with C2
system
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c r a f t i n g i n n o v a t i o n t o g e t h e rFactors Affecting SPI, OI and II of Air force Weapons
Weapon System Factors Affecting
SPI OI II
Close Air
Support /
Attack Helo
Deep Strike
Air Defense
Chaff, ECM,
ESM, Multi Mode
Radar, Precision
Guided Munitions
All of the above
and Inertial
Navigation
System
All of the above
and Look
Down/Look Up
Radar
Night Flight,
Night Time
Delivery, All
Weather
Operation
Inter Aircraft
& Ground
Station
Communicati
on
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c r a f t i n g i n n o v a t i o n t o g e t h e rFactors Affecting SPI, OI and II of Naval Platforms
Weapon System Factors Affecting
SPI IIOI
Battle Ships Intensity of
Threats faced,
Ability to detect
threatening
Platform,
Protection to
Evade hit,
Protection to
Evade Kill given
hit, Ability to
Jam/Confuse
Enemy Platform
Shallow
Water/ High
Seas
Operability
Communication
Links with Shore,
with Maritime
Aircraft, with Sub
Marine force, with
other Ships.
Submarine
Communication Links
with Shore, Maritime
Aircraft, Own
Submarine force.
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Combat Support Systems (CSS)
Intelligence Surveillance
& Reconnaissance(ISR)C4 Information
Warfare
Logistics
Support
System
Space based
Airborne
Sea Based
• Ground Based
Command and
Control
Communications
Computers
System Integration
EW
Opsec
Psyops
Deception
Lethal IW
Non lethal IW
Encryption
SW Engg
Networking
Computer
Security
Info Security
Infrastructure
Resources
Material
Management
National
Resources
Inter-service
Integration
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August 16, 2010 59© Crafitti Consulting Private Ltd.
IW
ILSS
Space
Air
Sea
Gnd
Cmd & Control
Communications
Computers
System Integration
ISRC4
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August 16, 2010 60© Crafitti Consulting Private Ltd.
I1 I2 I3 I4 C1 C2 C3 C4 W L
Space based ISR (I1) 1 1 1 1 1 0 0 0 1 1
Airborne ISR (I2) 0 1 1 1 1 0 0 0 1 1
ISR Sea based ISR (I3) 0 0 1 0 1 0 0 0 1 1
Gnd based ISR (I4) 0 1 1 1 1 0 0 0 1 1
Cmd and Control (C1) 0 0 0 0 1 0 0 0 1 0
C4 Communications (C2) 1 1 1 1 1 1 1 1 1 1
Computers (C3) 1 1 1 1 1 1 1 1 1 1
System Integration (C4) 1 1 1 1 1 1 1 1 1 1
IW (W) 1 1 1 1 1 1 1 1 1 1
ILSS (L) 0 0 0 0 1 0 0 1 0 1
I1 I2 I3 I4 C1 C2 C3 C4 W L
Space based ISR (I1) 1 0 0 0 0 1 1 1 1 0
Air ISR (I2) 1 1 0 1 0 1 1 1 1 0
ISR Sea based ISR (I3) 1 1 1 1 0 1 1 1 1 0
Gnd based ISR (I4) 1 1 0 1 0 1 1 1 1 0
Cmd and Control (C1) 1 1 1 1 1 1 1 1 1 1
C4 Communications (C2) 0 0 0 0 0 1 1 1 1 0
Computers (C3) 0 0 0 0 0 1 1 1 1 0
System Integration (C4) 0 0 0 0 0 1 1 1 1 1
IW (W) 1 1 1 1 1 1 1 1 1 0
ILSS (L) 1 1 1 1 0 1 1 1 1 1
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August 16, 2010 61© Crafitti Consulting Private Ltd.
Combat
Support
Systems
Combat
Support
System
Dependency
Indices (Di)
Combat
Synergy
Indices
(Si)
Sub System
Activity Index
Ai =(Di) X (Si)
CSS Normalised
Weights
(Wi)
Order of
Ranking
Space based ISR 0.064 0.083 0.00531 0.0598 VIII
Air based ISR 0.096 0.070 0.672 0.0757 IV
Sea based ISR 0.115 0.047 0.00541 0.0609 VI Gnd based ISR 0.096 0.070 0.00672 0.0757 IV
Cmd and Control 0.165 0.033 0.00545 0.0614 V
Communications 0.054 0.165 0.00891 0.1004 III Computers 0.054 0.165 0.00891 0.1004 III
System
Integration 0.076 0.165 0.01254 0.1413 II
IW 0.142 0.165 0.2343 0.2639 I
ILSS 0.138 0.039 0.00538 0.0606 VII
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August 16, 2010 62© Crafitti Consulting Private Ltd.
ISR C4
Space Based
Air Based
Sea Based
Ground Based
Command and Control
Communications
Computers
System Integration
IW ILSS
Country A Country B Country C
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August 16, 2010 63© Crafitti Consulting Private Ltd.
CSS Factors
ISR
Space based ISR Communications Satellites, Navigation Satellites,
Meterological Satellites, Imaging Reconnaissance Satellites,
Relay Satellites
Air baser ISR AWACS/AEW, Air based Ground Tactical Reconnaissance,
Maritime Reconnaissance, Airborne Ground Strategic
Reconnaissance, Airborne Battlefield Surveillance Capability
(UAV/RPV capability)
Sea based ISR Surface Tactical Recce, Sub-surface Tactical Recce, Strategic
Recce, Coast based Strategic Recce
Ground based
ISR
Tactical Recce, Air Space Recce, Strategic Recce
C4
Command and
Control
Strategic C2, Tactical C2, Politics Military C2, Inter Services
Integration
Communications Utilization of EM Spectrum, Communication System,
Communication Security, Merger with National Telecom
System
Computers Computing Power, Software capability, Knowledge
processing and Automated Decision Making Capability
System
Integration
Data Fusion, National Level Interoperability, Inter Services
Operability, Integration of ISR, C2, ILSS with Lethal
System, Fault Tolerant Communication / Computing,
Interoperability Standards
Information Warfare (IW) Operations Security, Psychological Operations, EW,
Deception Lethal IW, Non Lethal IW, Cryptology, Computer
Security, Info Security, Intelligence
ILSS Armed Forces Resources, Logistics Infrastructure, Material
Management, National Resources, Inter Service Integration
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Adaptive Dynamic Model (ADM)
• Off shoot of Lanchester Models
• J.M. Epstein
• Use of Exchange Ratio and
Prosecution Rate
• Parameters reflecting ability to
concentrate fire in engagements
• Uses Force strength instead of
Numerical Strength
• Withdrawal and reinforcements
• Close Air Support to Ground Forces
Extensions
• Air to Air Combat
• Naval Combat
including sub surface
• use of Weapon Power
Scores instead of
WEI for Force
Strength
• Estimation of
parameters based on
realistic data
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• Initial Force Strengths
of the Forces
• Force Strength
Reinforcement on each
day
• Force Strength Attrition
Rate
• Exchange Ratio
• Threshold Attrition
Rates
• Number of Close Air
Support (CAS) Aircraft
• CAS daily Sortie rate
per Aircraft
• CAS aircraft Attrition
rate per sortie
• Battle termination
Conditions
Force
Strength loss
and Aircraft
Attrition per
day
OUTPUT
INPUT
Adaptive
Dynamic
Model
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Equations of the Model :
,)1(111 tg
RAtDCASttg
Atg
A
,)1(11
11 t
gRDtACASt
gA
t
tt
gDt
gD
,
maxW
W(t)1 )( )(
t
gt
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)1( if )1( 1
)1(W )1(
)1( if 0
)(max
dT
dTddTd
dT
d
tttW
tW
t
tW
.)(
)1()1()(
)(t
gD
tg
RDtg
Dtg
D
td
We set W(1) = 0, on the attacker’s side
aT
ta
aT
tgTa
tg
tg
)1(
)1(
)1()(
,
)(
)1()1()1(
)(t
gA
tg
RAtg
Atg
A
ta
.
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We set g(1) equal to some initial value [g(1)
aT].
The ground-induced exchange ratio is givenby
,
)(g
A
)(
0 = )(
at
dtg
D
t
(8)
where 0 is a constant.
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Equations for Close Air Support (CAS)aircraft:
),( 1 )1(a
D = )( ta
RDdS
datt
aD
).(1 )1( = )( ta
RAaS
aat
aAt
aA
),( = )( ta
DatDCAS
, 1
1da
-1-1
=
da
dS
V
dKL
a
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),(A b = )( ta
tACAS
. 1
1
aa-1-1
=b
aa
aS
Va
KL
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SIDE A SIDE B
Ground Forces Ground Forces
CAS Forces CAS Forces
AD FightersAD Fighters
AD EscortsAD Escorts
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Test Scenario – Country A Strike
Corps attacking Country B holding forces
Force with
Country A
Force with
Country B
1 Armoured
Division
2 Infantry Division
1 Independent
Armoured Brigade
3 Independent
Armoured Brigades
3 Infantry
Divisions
1 Armoured
Regiment
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Total FS available (x1000)
Country A
1 Armoured Division + 3 Infantry Division + 1Independent Armed Bde = 910.6 + 3 x 184.5 + 359.9 = 1824
Country B
2 Infantry Division + 3 Independent Armed Bde + 2Armoured Regiments = 2 x 152.3 + 3 x 266.2 + 88.7 = 1191.9
Force Strength Ratio (FSR (A/B)) = 1.53
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Mobilizations Schedule
Ith
Day Country A (Attacker) Country B (Defender)Force FS
(x1000)Force FS
(x1000)1 2 Infantry Division
= 2 x 184.5369 2 Infantry Bde + 1
Integral ArmedRegt = 2 x 1/3 x152.3 + 1/3 x266.2
190.3
2 2 Armed Bdes =2 x 359.9
719.8 2 Armed Bde + 1Inf. Bde = 2 x266.2 + 1/3 x152.3 = 532.4 +50.8
583.2
3 Armoureddivision -Armoured Bde =910.6 - 359.9
550.7 1 Armed Bde =266.2
266.2
4 Infantry Division 184.4 1 Infantry Division 152.3
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Results of Test Scenario
o=2.0 a = d = 0.035
Day FSattacker
(remaining)
FSdefen
der(remaining)
Threshold
attacker
Threshold
defender
FSR
1 369.00 193.10 184.50 127.50 1.93902 1041.16 583.56 520.58 390.99 1.78423 1527.58 675.61 763.79 452.66 2.26104 1613.37 656.90 806.69 440.12 2.45615 1501.68 496.89 806.69 440.12 3.02216 1395.64 354.74 806.69 440.12 3.9343
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Performance IndexATK (A) DEF (B)
TFS (a) 1823.9 1192RFS (b) 1395.64 354.74FSL(a-b) 428.26 837.26
FSL/TFS (X) 0.235 0.70PI = X(B)/X(A) 0.70/0.235 = 2.99
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The Future
An Information Theoretic
Approach to Estimate Threat
Intensity Distribution in
Network Centric Combat Force
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INFORMATION
GATHERING NODES
•SATELLITE
SURVEILLANCE
•AD RADAR
•AIRBORNE EARLY
WARNING
•UAV, etc
NETWORK CENTRIC COMBAT FORCE
DATA FUSION NODECOMMAND AND
CONTROL NODE
AIRBORNE EARLY WARNING
SATELLITE
SURVEILLANCE
LOGISTICS NODE
COMBAT NODES
BATTLE DAMAGE
ASSESSMENT NODE
UAV
AD
RADAR
SENSOR INFO.
COMM. LINK.
ENEMY FORCES
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THREAT INTENSITY (T) VS COMBAT SUPPORT SYSTEM EFFECTIVENESS
RATIO (k)
T = exp(- k x FSR )
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
00.
20.
40.
60.
8 11.
21.
41.
61.
8 22.
22.
42.
62.
8 3
Combat Support System Effectiveness (f/e) (k)
Th
reat
Inte
nsi
ty
(T)
Force Strength Ratio = 0.5 Force Strength Ratio = 1.0 Force Strength Ratio = 1.5
Force Strength Ratio = 2.0 Force Strength Ratio =2.5 Force Strength Ratio = 3.0
THREAT INTENSITY (T)
T = f (FS, CSS) for friendly and Enemy force
= e-k * FSRk = Ratio of CSS
FSR = Ratio of FS
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New Modelling Approaches for Combat
Petri Nets
Cellular Automata
Artificial Life
Chaos/Catastrophe Theory
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© Crafitt
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Some terms
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Real World Networks
• Social Networks: Set of people or groups of people with some pattern of contacts or interactions between them
• Information/Knowledge Networks: How information units are linked – e.g. Citation Network of academic papers OR World Wide Web
• Technological Networks: Man-made networks designed for distribution of some commodity or information. Electric Power Grid, Railways
• Biological Networks: Food web, Blood Vessels
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Network Centric Operations
NCO is a theory which proposes that the application of information age concepts to speed communications and increase situational awareness through networking improves both the efficiency and effectiveness of military operations.
August 16, 2010 83© Crafitti Consulting Private Ltd.
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© CRAFI
Social Computing and Social Network Analysis
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© CRAFI
Social Computing (Wikipedia)• Social computing is a general term for an area of computer science that is concerned with the
intersection of social behavior and computational systems.
• In the weaker sense of the term, social computing has to do with supporting any sort of social behavior in or through computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology. Thus, blogs, email, instant messaging, social network services, wikis, social bookmarking and other instances of what is often called social software illustrate ideas from social computing, but also auction software and other kinds of electronic market or electronic negotiation platforms where people interact socially.
• In the stronger sense of the term, social computing has to do with supporting “computations” that are carried out by groups of people, an idea that has been popularized in James Surowiecki's book, The Wisdom of Crowds. Examples of social computing in this sense include collaborative filtering, online auctions, prediction markets, reputation systems, computational social choice, tagging, and verification games.
• Social computing has become more widely known because of its relationship to a number of recent trends. These include the growing popularity of social software and Web 2.0, increased academic interest in social network analysis, the rise of open source as a viable method of production, and a growing conviction that all of this can have a profound impact on daily life
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© CRAFI
Social Networks• Graphs representing social relationships between
people or organizations
• Each Node is a person or actor
• An edge connecting two nodes is also called a tie and represent a social relationship
How can we Draw this Network for 1 Million people?
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© CRAFI
Building a Social Network• How to gather data for building a social network?
• Two Main Approaches
• Elicitation – Questionnaire/Survey
• Registration – Registered information – emails, membership lists
• Elicitation – old method is inaccurate and costly
• Registration is more useful and scalable
• Especially with online networks
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Properties of Networks
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Random Graph
© Crafitt
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• Mathematicians have studied these extensively
• Undirected edges are placed at random between a fixed n vertices
• Maximum edges possible = (n/2) (n-1)
• In a random graph each edge is independently present with a probability p
• Degree of the vertex is distributed according to a binomial or Poisson distribution
Real life Networks appear to be Non-random – leading to explanations about network formation and emerging structures
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Milgram’s Experiment – Six Degrees of Freedom
• In mid-sixties Stanley Milgram, a social psychologist teaching at Harvard, with a reputation of doing original experiments, conducted an innocuous experiment which by his standards was rather boring to say the least. He asked 160 volunteers to send a letter to his stockbroker friend in Boston. The only condition was to send the letters not directly to the stockbroker but to their own friends, whom the volunteers think are most likely to know the stockbroker. Each of the friends was asked to send this further in the same manner.
• Surprisingly, the letters arrived to the stock broker in an average six-hops or six-degrees. This led to the notion of six-degrees and of small world – that all of us are connected to each other by six intermediate connections. We all are connected to a small subset of people, which is true. It is also a fact that each of our connections is not mutually exclusive. They connect with each other as well. In effect, our connections are clustered. This leads to a problem, world can’t be both – a small world and a clustered one.
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HOW CLOSE YOU ARE TO BARACK OBAMA?
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Small-World Effects
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• Most pair of vertices in most networks seem to be connected by a short path through the network
l << n
How fast rumors spread in a network?
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Transitivity or Clustering
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• A friend of your friend is most likely to be your friend as well!
• How many triangles does the Network has
Clustering Coefficient
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Key Properties of Interest
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Minimally Connected Networks- Properties
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N=16; Arcs = 15 => Arcs/N = 0.94
Minimally Connected Network – Nodes are all connected with the minimum number of links possible
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Maximally Connected Network – Every Node is directly connected to every other node
Maximally Connected Networks - Properties
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Random Network– Unpredictability in the network
Random Network- Properties
Links are distributed randomly
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Regular Network– Uniform clustering
Regular/Lattice Network- Properties
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Small World Network– A Minor rewiring of Regular Network
Small World Network- Properties
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Random Network with Growth – A Minor rewiring of Regular Network
Random Network with Growth- Properties
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Scale Free Network with preferential attachment – A very adaptive network
Scale Free Network with preferential attachment - Properties
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Network Comparison
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Network Comparison
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Social Scientists Classification of Social Networks
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Ego-Centric Networks Socio-Centric Networks Open-System Networks
Networks that are
connected with a single
node or individual
Boundaries of the
network are clear;
Networks in a Box
Boundaries are not
necessarily clear
Example, My good
friends, All companies
doing business with ABC
Example, students in a
class, employees of an
organization
Example, network of
elite class, connections
between corporations
Lists alone are
insufficient – info about
connections also is
required
Most studied in terms of
fine points of network
structure
Most interesting and
most difficult to study
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Social Network Archetypes
Type Customized Response Modular Response Routine Response
Problems and
Solutions
Ambiguous Known components –
but combination or
sequence not known
Well-defined and
predictable
Value Quickly framing and solving
a problem in an innovative
way
Delivering a unique
response depending
upon the constellation
of expertise required
by the problem
Efficient and consistent
response to a set of
established problems
Types New product dev,
investment banks, Strategy
consulting
Surgical teams, Law
firms, B2B sales
Call centers, insurance
claims processes
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Taxonomy of Network Centric Warfare Architectures
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Architecture Characteristics
A. Centralized One central high value Hub – other low value nodes networked
and controlled by Hub
B. Hub-Request “Type E” Request based plus one or more central high value hubs
C. Hub-Swarm “Type G” Swarming plus one of more central high value hubs
D. Joint Mixture of other six types (Type A, Type B, Type C, Type E, Type F
and Type G)
E. Request-Based Nodes of same value, but with different specialized capabilities.
Request for service between nodes of different kinds
F. Mixed Mixture of “Request-Based” and “Swarming”
F1: Limited Types Small number of node types (includes the case of separate sensor,
engagement, and C2 grids”
F2: Commonality Nodes are different, but have significant commonality
G. Swarming Nodes identical or nearly so
G1: Emergent Swarming Nodes follow simple rules, like insects
G2: Situationally Aware
Swarming
Nodes share information to build up Situational Awareness
picture
G2(a): Orchestrated One node is a temporary “leader”
G2(b): Hierarchical Nodes are arranged in a Hierarchy
G2(c): Distributed No Leader or Hierarchy
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Combining these three classifications – we propose following 5 type of social networks
• Customized Response Open Swarms (CROSs) Networks
• Modular Response Socio-Centric Request-Based (MRSR) Networks
• Routine Response Ego-Centric Centralized (RECC) Networks
• Customized Response Socio-Centric Hub-Swarm (CuSHuS) Networks
• Customized Response Open Request-Based (CROR) Networks
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OPEN QUESTION?????
Network Centric Warfare –
A Revolution in Search of Doctrine
August 16, 2010 108© Crafitti Consulting Private Ltd.
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NCW Military Doctrine
Military Doctrine is defined as a comprehensive system of views and procedures for conduct of future wars including various military operations, established by military experts, technologists and armed forces, in the likely threat environment, and within the purview of present force structures.
The doctrine is subject to periodic reviews and analysis and is evolved taking into account the dynamic geo-political, economic and technological trends in the world scenarios. Also such a doctrine should be freely available as a comprehensive document, so as to give a common basis for decision making at all level of military and defense hierarchy of the nation.
August 16, 2010 109© Crafitti Consulting Private Ltd.
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National Security Doctrines
August 16, 2010 110© Crafitti Consulting Private Ltd.
Doctrines
Domain Aim(s)
1. POLITICAL DOCTRINE
International Relations
Foreign Policy
Diplomacy
Politics
How to Avoid war
If imposed, how to support war
2. MILITARY DOCTRINE
Army
Navy
Air Force
Space Force
Joint Operations
How to wage war
3. ECONOMIC DOCTRINE
Economic Policy
Industrial Policy
How to support and sustain war
4. INTELLIGENCE DOCTRINE
Intelligence Agencies
Analysis Agencies
How to collect, process and disseminate information for timely decision making
5. WMD DOCTRINE NBC Policy
Peaceful Nuclear Uses
How to deal with enemy’s WMDs and deploy own WMD
6. SPACE DOCTRINE
Space Plans
Communication, Reconnaissance & Spy Satellites
Launch Vehicles
How to support (1) - (5) by providing near real time information to analysts
7. CYBERPACE/ INFORMATION
WARFARE DOCTRINE
Cyber Space
Audio Visual & print Media
Propaganda
Propaganda in cyberspace
Counter enemy propaganda
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The Changing Battlefield – from Linear Battlefield ….
August 16, 2010 111© Crafitti Consulting Private Ltd.
Logistic Supply
Centre
Strategic Reserve
C2Centre
FWD Deployed Force
Mobile
Attack with
Armour
Enemy FWD
Deployed
Force
Border
Enemy
Mobile
Reserve
Fig. 1. Traditional Linear Battlefield
( Sequentially dealing with each of enemy’s force component)
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Strategic Reserve
C2Centre
FWD Deployed Force
Traditional
Armour
Advance
FWD
Deployed
Force
Border
Mobile
Reserve
Fig.2. Air Land Battle Doctrine
( Increased Non-Linearity)
Air Attack
on Follow
on Force,
Strategic
Reserves
and C2
Centre
The Changing Battlefield – to Air Land Battle Doctrine ….
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Anti ISR Attack
Anti C4 Attack
Anti EW Attack
Anti ILS Attack
Strategic Attack
Attack against enemy
Mobile Unit
Attack Levels
Border
FWD Deployed
Highly Mobile
smaller Units
(screen force)
Airborne Surveillance
Systems
Automated
PG Long Range
Missile
Mobile C4 ISR
Centre
Enemy
Fig. 3. Future Doctrine (Highly Non-Linear)
Mobile Armoured Units
The Changing Battlefield – to Non-Linear Network Centric Battlefield ….
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Key Features of the NMD
Catering for Unanticipated Threats
Knowledge Based
Flexible
Timely
Highly Trained Manpower
Accurate BDA
The Changing Battlefield – to NCW Doctrine Features ….
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Key Features of NMD
• NMD should cater for ‘unanticipated threats’. Gone are the days when it was possible to clearly point out one’s friendly and enemy nations. In the new world order, no country has permanent friends or foes. It is only the interests of the country that have permanent nature. Therefore, a nation should be prepared to deal with ‘unanticipated threats’ from unknown quarters.
• Intelligence/Information and knowledge should be the basic building block of the NMD. Troops, units and military organisations should be trained and structured to treat information and knowledge as the basic tool of fighting wars. These should be armed with processes and equipment for speedy collection, processing and dissemination of information/intelligence and knowledge.
• NMD should be flexible enough to take care of multitude of varied threats with different levels of sophistication e.g. the high mobility armoured units based doctrine may not work against Guerrilla’s or terrorists in an LIC (Low Intensity Conflict), but will have excellent performance against conventional multi-layered defence layout.
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Key Features of NMD
• Forces, logistics and communications should have ‘Just in Time’ capability. Bringing out forces needed to destroy an enemy as soon as the need arises is the crux of the problem. If the enemy is made to believe that the friendly forces are omnipresent, it will be extremely difficult for the enemy to attack, however strong the enemy may be.
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Key Features of NMD
• Despite all the technologies, it is the man beside the machine who counts. The NMD should start with a well balanced training of troops and commanders. The future battlefields will require agile leaders. These commanders must be capable of rapidly formulating concepts, planning operations, making decisions and pressing the fight. Agile leaders who quickly and accurately apply the conditions of their environment much faster than the enemy will produce decisive victories. Therefore, proper, continuous training programs based on automated battlefield systems for military commanders are needed. Quality of leadership in terms of training, motivation and innovativeness will decide the wars of future. The burden on the military soldier who will actually pull the triggers will increase manifolds. These soldiers should be trained to handle multiple weapons in various terrains, environment conditions and jointly with other forces. Manpower development is the basis of the NMD.
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Key Features of NMD
• NMD should be based on accurate and timely Battle Damage Assessment (BDA) on the enemy. If a first strike is successful against an enemy, there is no point in going for second and third strikes. The resources can be better utilised by going to the next task. In earlier warfare, BDA was a luxury but in future wars it will be a necessary activity as it gives the option of using one’s forces in a much more flexible way. BDA helps the commanders to allocate means, commit collection assets and execute collection plans. Timely, accurate and continuous BDA is the key feature of the NMD.
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August 16, 2010 119© Crafitti Consulting Private Ltd.
S.No. Threat Countered By
1 Low Intensity Conflict/Guerrilla
Warfare/Insurgency
Intelligence/Propaganda/
counterinsurgency Doctrine
2. Traditional Face to Face Attrition warfare based
military deployment (Ex. Soviet Union multi-
layered defence layout)
Highly Mobile Tanks/Armour Penetration Units
based doctrine
3. Mobile armour/tank penetration doctrine Airland Battle Doctrine/Follow on Forces Attack/
Strike Deep Strike Hard
4. Air Land Doctrined Forces SEW, PGMs integrated in C4ISR system backed by
RMA technologies
5. RMA backed Joint force doctrined forces Combination of SEW and PGMs at Strategic level
backed up by very small units capable of disrupting
enemy’s lines of Communications, C2 system and
capable of
disinformation/camouflaging/Information Warfare
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A New Integrated Armed Structure called SLAP
SLAP (Sea Land Air and sPace) force
The small, independent, information warfare capable units should be linked together through a series of multi-purpose, redundant, reliable, fault tolerant
and intelligent communications links, C2 nodes, logistics support links and SEW links.
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Platoon Information Combat and Kill
August 16, 2010 121© Crafitti Consulting Private Ltd.
ORGANISATION OF PICK
Arms Section Information Warfare Section C4ISR Section
A1. Anti Air Weapons
Portable SAMs
Portable Anti Missiles Missiles
B1. UAV unit
Short and Medium range
information collection
Short range strike capability
C1. Liaison Unit
Computerised Connections with
other PICKs
A2. Anti Armour Weapons
Anti Tank Missiles
Anti Tank Guns
B2. EW unit
Electronic Jammers
ECCM Systems
ESM systems
C2. Signals Unit
Mobile computing based, multi
media based system
Uses GPS
A3. Anti Personnel Weapons
Light Weight Mortars of high
calibres capable of firing smart
munitions
Dual use rapid fire guns for long
range (sniper fire) and short
range fights.
C3. Analysis Unit
PICK HQ
C2 centre
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NCW Doctrine has to be based on Swarming and Spiral Swarming
Swarming is achieved when the dispersed nodes of a network of small (and alsoperhaps some large) forces can converge on an enemy from multiple directions,through either fire or maneuver. The overall aim should be sustained pulsing -Swarm networks must be able to coalesce rapidly and stealthily on a target, thendisserver and redisperse, immediately ready to recombine for a new pulse.
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Doctrine of Spiral Swarms
• To defeat an already networked force – which acts through swarming – we need to develop very complex Spiral Swarms – Swarming the Swarms Doctrine
August 16, 2010 123© Crafitti Consulting Private Ltd.
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Crafitti Consulting
Crafting innovation together . . .
www.crafitti.com
Navneet Bhushan ([email protected])
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